Simple Regression Analysis and Correlation

These flashcards cover essential concepts from simple regression analysis and correlation, highlighting key objectives and statistical methods relevant for understanding and analyzing regression models.

What is the Pearson product-moment correlation coefficient used for?

To determine if there is a correlation between two variables.

What are the independent and dependent variables in regression analysis?

The independent variable is the predictor (x), and the dependent variable is the one being predicted (y).

What does the slope of the least squares regression line represent?

The amount of change in the dependent variable for each one-unit change in the independent variable.

What is the purpose of calculating residuals in regression analysis?

To determine the fit of the model, identify outliers, and test regression model assumptions.

How is the standard error of the estimate calculated?

It is calculated using the sum of squares of error.

What does the coefficient of determination (r2) indicate about a regression model?

It measures the proportion of variability in the dependent variable that is explained by the independent variable.

What hypothesis tests can be used to examine the slope of the regression model?

The t-test and F-test are used to test hypotheses for both the slope and overall regression model.

What are confidence intervals used for in regression analysis?

To estimate the conditional mean of the dependent variable.

What is the trend line equation in regression forecasting?

It estimates future outcomes based on historical data and is derived from the regression model.

How do you test for the significance of a regression model?

Using the t-test and F-test along with their associated p-values.